Cosmose provides an Attention-as-a-Service platform that runs proprietary AI inference on mobile devices to select and display personalized content on the lock screen and other native UI layers. By processing first‑party signals locally, the solution delivers sub‑100 ms, privacy‑preserving prompts for brands, advertisers, and app developers via iOS/Android SDKs and secure APIs. The architecture eliminates data exfiltration, reduces latency, and supports compliance with GDPR and CCPA.
Funding
Funding not disclosed
Founders
Product
Problem
Mobile users receive generic notifications that often get ignored, while brands struggle to deliver timely, relevant content without compromising user privacy. Existing solutions rely on cloud processing, exposing personal data and introducing latency that degrades the user experience.
Solution
Cosmose offers Attention-as-a-Service, a platform that uses proprietary AI models and first‑party data to surface personalized experiences directly on the smartphone lock screen and other high‑visibility touchpoints. The MindMentor engine runs inference locally on the device, enabling real‑time content selection without transmitting raw user data to external servers. By keeping computation on‑device, the solution maintains strict data privacy, reduces latency, and conserves network bandwidth. Enterprises can integrate the service via SDKs or APIs to deliver context‑aware prompts, offers, or information that align with each user’s current intent and environment.
Target Audience
The primary customers are consumer brands, mobile advertisers, and app developers seeking to increase engagement through privacy‑preserving, lock‑screen–based experiences on iOS and Android devices.
Features
- MindMentor attention engine that ranks and selects content in real time on the lock screen and other native UI layers
- Fully on‑device AI inference using optimized neural networks, ensuring zero data exfiltration and sub‑100 ms response times
- Integration of first‑party behavioral and contextual signals (e.g., app usage, location, time of day) to drive personalization
- SDKs for iOS and Android with plug‑and‑play modules that require minimal code changes for developers
- Secure API for enterprise back‑ends to push content catalogs and retrieve aggregated engagement metrics without exposing raw user data
- Adaptive power‑management that throttles model execution based on battery state and device performance constraints
- Compliance‑ready architecture supporting GDPR, CCPA, and other privacy regulations through on‑device data residency